Engagement Guide

Which engagement is right for you?

Three productized engagements. Pick by where you are — discovery uncertainty, defined use case, or ongoing capacity — not by what they cost. Pricing overlaps because what differentiates them is what's included.

Compare side-by-side

The decision matrix

Screenshot for your CFO. Or scroll past for tier detail.

All prices "From" — final scope and investment confirmed in SOW after the discovery call.

	AI Enablement Sprint Most Popular	Rapid AI Development	Fractional AI Team
Best when	You have a problem; need help scoping the AI use case AND building it	Use case is defined; you need senior engineers to build it now	You need ongoing AI engineering capacity, not a one-off project
You provide	A business problem and an executive sponsor	A defined use case and technical spec	A roadmap of work and a product owner on your side
We deliver	Discovery + build + governance review + team handoff	Architecture, build, integration, deployment — no discovery phase	Embedded engineers, advisor hours, or fully scoped retainers
First deliverable	AI Opportunity Roadmap (Wk 2)	Working prototype (Wk 3–4)	First sprint output (Wk 1–2)
Timeline	10–12 weeks	6–10 weeks	3–12 months
Investment	From $85K	From $50K	From $15K / month
Engagement model	Fixed scope, fixed price	Fixed scope, fixed price	Monthly retainer
	See detail	See detail	See detail

AI Enablement Sprint

Rapid AI Development

Best when: Use case is defined; you need senior engineers to build it now
You provide: A defined use case and technical spec
We deliver: Architecture, build, integration, deployment — no discovery phase
First deliverable: Working prototype (Wk 3–4)
Timeline: 6–10 weeks
Investment: From $50K
Engagement model: Fixed scope, fixed price

See detail

Fractional AI Team

Best when: You need ongoing AI engineering capacity, not a one-off project
You provide: A roadmap of work and a product owner on your side
We deliver: Embedded engineers, advisor hours, or fully scoped retainers
First deliverable: First sprint output (Wk 1–2)
Timeline: 3–12 months
Investment: From $15K / month
Engagement model: Monthly retainer

See detail

AI Enablement Sprint

Timeline: 10–12 weeks

Investment: From $85K

Best for: Mid-market and enterprise teams that have a business problem, are convinced AI is part of the answer, and want one engagement that takes them from problem-scoping to a production-ready system with their team trained to operate it.

What you get:

AI Opportunity Roadmap with ROI estimates (Phase 1)
Working production-quality system on your data (Phase 2)
Production hardening: error handling, observability, cost controls (Phase 3)
Security validation memo for your security team (Phase 3)
Team enablement: runbook, model criteria, fallback policies, cost ceilings (Phase 4)
Production deployment + rollback plan

Recent build: A veterinary healthcare client went from zero AI to production in 10 weeks. SOAP-note documentation time dropped 50–60%, unit cost landed at $0.23 per summary (vs. $3–$5 from commercial vendors). Director of Technology quote and full case study on /proof.

Best paired with: an executive sponsor who can dedicate 2–4 hours per week. If you don't have sponsor commitment, we'll tell you to wait until you do.

Discuss Your Challenge See the methodology

Rapid AI Development

Timeline: 6–10 weeks

Investment: From $50K

Best for: Teams with a defined use case and a technical spec who need senior engineers to build the system now. No discovery phase, no roadmap deck — straight to architecture and code.

What you get:

Architecture and solution design
Build, integration, and deployment to your accounts
Production hardening (error handling, observability, cost controls)
Documentation and team handoff

Examples we've built:

Custom LLM application for legal document analysis ($85K, 8 weeks)
Intelligent customer inquiry routing system ($65K, 6 weeks)
Automated data enrichment pipeline ($120K, 10 weeks)
Multi-agent research assistant ($95K, 8 weeks)

Best paired with: a product owner or technical lead on your side who can answer architecture questions within a business day. If you need help defining the use case first, the AI Enablement Sprint is the right starting point.

Discuss Your Challenge See built examples

Fractional AI Team

Timeline: 3–12 months

Investment: From $15K / month

Best for: Enterprises that need ongoing senior AI engineering capacity — extending their internal team without a full-time hire, advisor coverage at the leadership level, or both.

AI Advisor

$15K / mo

~20 hours / month

Strategic guidance, AI roadmap reviews, and architecture sign-off for your existing team.

Embedded Team

From $25K / mo

80+ hours / month

Senior engineers embedded with your team for ongoing build velocity. Stand-ups, sprint cadence, your tooling.

Custom

Scoped

Flexible engagement

Specialist coverage, multi-team rollouts, or program-level engagements at enterprise scale.

Best paired with: a clear product owner on your side and a roadmap of work for the next 90 days. If you're still scoping the first use case, start with the Sprint instead.

Discuss Your Challenge

For your procurement team

What's in a typical SOW

Eight things every FusionLeap SOW covers. Bring this to your CFO, security lead, and counsel before the discovery call so they can flag concerns early.

Scope of work

Concrete deliverables, in-scope vs. out-of-scope, acceptance criteria.

Timeline & milestones

Phase boundaries, weekly demo cadence, hand-off date.

Pricing & payment terms

Fixed price for Sprint and Rapid Dev, monthly for Fractional. Net 30 standard.

IP ownership

Client owns all custom code, models, prompts, and documentation. We retain rights only to FusionLeap platform tooling.

Compliance scope

Engineering responsibility (us) vs. legal/audit responsibility (your team). The canonical compliance clause.

Change control

Process for scope changes mid-engagement. Expansion riders for in-flight scope growth.

Confidentiality & security

Mutual NDA executed pre-SOW. Sub-processor list disclosed. Data handling per your security team's spec.

Termination & handover

Convenience and for-cause provisions. Deliverables-to-date hand-off included by default.

We'll walk you through every clause line-by-line during the discovery call. The full SOW is tailored to your engagement before kickoff.

FAQ

The questions buyers actually ask

Procurement, security, and engineering questions we answer up front so they don't derail the engagement.

How are you different from a Big-4 firm?

Big-4 engagements typically open with a 6–12 week strategy phase that produces a deck. Our first deliverable is working software running on your data. We staff each engagement with the engineers who will write the code — not a partner-and-pyramid model. Pricing is transparent and disclosed on this page.

We have an internal AI team — why would we hire FusionLeap?

Most internal teams are throughput-bound, not capability-bound. We typically embed alongside your team for one production use case, transfer the patterns and tooling, then leave. Your team owns the codebase from day one.

How do you handle data security and regulated industries?

We design data flows, audit trails, model logging, access controls, and PII boundaries that pass review by your security, compliance, and legal teams. We've shipped systems in environments under HIPAA, FERPA, GDPR, and SOC 2 review. We don't act as your DPO, counsel, or auditor — we engineer to their spec.

Who owns the IP we build together?

You do. Our standard engagement transfers all custom code, models, prompts, and documentation to your organization at delivery. We retain rights only to our own platform tooling (covered explicitly in the SOW). Any patent-pending architecture references are to FusionLeap's own internal cost-analysis platform, not to client work.

Can you work in our existing AWS / Azure / Anthropic / OpenAI accounts?

Yes. Default deployment is to your cloud accounts, your model provider accounts, and your version control. We bring engineering, not infrastructure lock-in.

What's the smallest engagement you'll take?

Our entry point for a production build is the Rapid AI Development engagement starting at $50K. For teams that aren't yet sure of the use case, we recommend the AI Enablement Sprint.

Do you sign MSAs, MNDAs, DPAs, and respond to security questionnaires?

Yes. Mutual NDA at the discovery call. MSA + SOW before kickoff. DPA where applicable. Standard security questionnaire turnaround is one week.

What happens after the engagement ends?

By the last week, your team is operating the system independently. We offer an optional Fractional AI Team retainer for ongoing capacity, but it is not a dependency we engineer in.

Still not sure which engagement fits?

That's what the 30-minute Architecture Review is for. We'll listen to your problem, tell you which engagement is the right answer (or whether we're even the right partner), and what the first 90 days would look like.

Discuss Your Challenge